Introduction

Today’s enterprises are facing fierce competition from domestic and foreign organizations [1]. To that end, the development of new products and services is the core activity of an organization’s competitive strategy, which includes concept design and the successful development of new products that can be launched in the market. While enterprises come under pressure to develop innovative products, the process of new product development and innovation (NPD) is extremely challenging [2]. Statistics show that the NPD failure rate for the established firm is 40% to 65%, while for startup companies it even exceeds 90% [3, 4]. Scholars estimate that approximately 3000 original ideas are needed to produce a successful new commercial product [5].

In a wave of entrepreneurship, the commercialization of business ideas has become both a core issue and a major challenge. Although existing research has generated a wealth of knowledge in NPD area, prior work generally shares a commonality of being set in the context of the firm level. Compared with other subjects in the field of business management, such as marketing, entrepreneur-ship, and social responsibility, studies on the development and teaching methods of NPD courses are relatively limited [6]. According to a survey on technology management courses by Mallick and Chaudhury [7], scholars and administrators both agree that NPD is one of the key knowledge and skills. The coverage of NPD has been continuously expanding across various fields, including, but not limited to, innovation, product design, finance, teamwork, manufacturing, and marketing. The development of new products and services is a complex process, which is why it is so difficult for scholars to design a curriculum that suits a practical purpose. However, the majority of current NPD textbooks available to the public fail to meet the current requirements of innovation and practical guidance, and therefore, do not satisfy the demands of business society.

To fill this gap, the study aims to disclose key components of NPD curriculum for this emerging issue by considering the research topics of extant journal articles so as to educate students becoming a creative individual who possesses knowledge, skills, and enthusiasm to bring an idea from conceptualization, idea generation, and finally to idea implementation. As NPD related courses gain increased interests in higher education institutions (HEIs), the study intends to provide some guidelines for program and curriculum design in business schools. In particular, we seek to answer the following two questions:

  1. (1)

    What are the educational objectives should be drawn up in the NPD course?

  2. (2)

    Which key components should be included in the innovative NPD curriculum?

The rest of the paper is organized as follows: we first review the background related to this study. We then introduce research method. Finally, we discuss the implications of our findings for NPD curriculum design and provide directions for future research.

Background

New Product Development (NPD) for Entrepreneurship

As defined by Fixson [1], new product development consists of nine stages, namely ascertaining opportunity, investigating market and user, creating idea and concept, refining and choosing conception, designing the product, building prototype, testing, evaluating financial capacity, and introducing marketing. The NPD process, hence, is often viewed as a flow that integrates the various phases from conceiving and transforming new ideas to delivering commercialize products [8]. The lifecycle of a consumer product generally encompasses four stages, namely introduction, growth, maturity, and decline. Theoretically, in the final stage of the lifecycle, the sales volume of the product will decrease gradually and it should be terminated when it is unprofitable for the company [9]. To keep pace with the competitors, companies should introduce new products with high quality, and innovativeness with shorter time to market. Also, a previous study found that regularly launching a new product is a crucial strategy for a company that attempts to survive in extremely competitive and fragmented markets [10]. Additionally, the first step of developing a successful product is to comprehend variables of the targeting market, such as consumer needs, economic situation, demography, technology, and political and legal shifts [11].

It cannot be overemphasized that new product development plays an essential role in innovation, which is the engine of growth in today’s marketplace [12]. The pressures to innovate are relentless, and highly innovative companies usually make more profit than less innovative companies [1]. Innovation generally involves five states, namely creating the idea, research, and development, building prototype, production and delivery, marketing and sales [13]. From the stake-holders’ view, innovation is a value-added process that through developing novel products, services, manufacturing procedures, and solutions. However, without entrepreneurial activities exploiting opportunities when they emerge in organizations, innovation remains little more than enthusiasm, rather than an objective goal [13].

Entrepreneurship is the driving force for promoting innovation and competitiveness in response to globalization and the development of technology. Prior research stressed entrepreneurship not only as a foundation to underpin innovation but also as a vital element for innovation [13]. Entrepreneurship was defined as an effort in promoting innovation in an ambiguous situation. Within the innovative process, the primary roles of entrepreneurship are to challenge extant rules and regulations, to evaluate new opportunities, to allocate and exploit re-sources, and to keep the innovation process moving forward [14]. Therefore, entrepreneurship education (EE) in higher education institutions (HEIs) gains increased interests because exerting EE on learners is beneficial to their pursuit of knowledge and skills as well as increasing intention becoming entrepreneurs [15]. Entrepreneurship education is generally categorized into three approaches [16].

  1. (1)

    Teaching “about” entrepreneurship means a content-laden and theoretical approach aiming to give a general understanding of the phenomenon. It is the most common approach in higher education institutions.

  2. (2)

    Teaching “for” entrepreneurship means an occupationally oriented approach aiming at giving budding entrepreneurs the requisite knowledge and skills.

  3. (3)

    Teaching “through” entrepreneurship means a process-based and often experiential approach where students go through an actual entrepreneurial learning process.

The majority of scholars today now agree that learning through own experience is the best way to learn to become an entrepreneur [16,17,18]. Entrepreneurs are uncommon learners who acquire knowledge and skill by doing, from the surrounding, and person, such as customers, suppliers, competitors and employees [19]. In addition, Lackéus [20] stated that the learning-by-doing is that one learns by experience in which include coping, experiment, problem-solving and opportunity taking and by learning from making mistakes. Learning-by-doing as an important approach to experiential education, which has emerged as the preferred methodology in higher education [21]. Consistent with this context, the study considers that learning-by-doing is a feasible pedagogic method for designing NPD curriculum.

Bloom’s Taxonomy and Educational Framework

Bloom’s Taxonomy was initially proposed by Benjamin Bloom in 1956 for guiding educators to design more appropriate curricula and to enhance students’ learning performance [22]. In the framework, the educational objectives are classified into three domains, namely affective, psychomotor and cognitive domains. The affective domain narrates the interactions between learners and educators who draw up objectives to induce awareness, attitudes, emotions, and feelings. In the psychomotor domain, the educational objectives are identified and categorized about physical manipulation of tools or instruments. The cognitive domain, which has been widely researched in many disciplines, consists of the hierarchy of sub-levels including knowledge, comprehension, application, analysis, synthesis, and evaluation [23]. Besides, this framework stresses that learning occurs at six levels of cognition: knowledge, comprehension, application, analysis, synthesis, and evaluation.

However, the original Bloom’s Taxonomy possessed some shortcomings and given cause for criticism; thus the revised Taxonomy was proposed in 2001 [22]. In Bloom’s Revised Taxonomy, the verb and none represent the process of cognitive dimension and the knowledge base respectively which allow the use of more information to define educational objectives and planning activities [23]. As shown in Table 20.1, the educators in HEI can apply Bloom’s Revised Taxonomy to draw up educational objectives and to design an appropriate curriculum, as well as the framework facilitates students clarifying their purpose [24].

Table 20.1 Bloom’s revised taxonomy
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Research Method

Data Collection

The study retrieved the textual data from the Scopus, which is one of the most extensive peer-reviewed research repositories in the Social Sciences, by searching the keywords of “new product development” or “new product design” or “new product innovation”, which was determined by relevant experts in the field. Next, the criteria from the previous study [25] were adopted to filter the article source and to select six journals that have the highest usage scores of NPD related articles in Scopus. There is a total of 221 articles, published from 2015 to 2019, were extracted, and their title, abstract, and keywords were downloaded for furthering analysis. The outline of data sources and subject areas was summarized in Table 20.2.

Table 20.2 Distribution of NPD journal articles by subject area
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Data Analysis

The study conducted the Latent Semantic Analysis (LSA) on a corpus of documents each represented by the title, abstract and keywords of the documents. LSA is especially appropriate for this study because NPD is characterized by many specific vocabularies in a complex manner and possessed latent concepts in this context [26]. However, traditional word-counting text mining approaches, count the word frequency merely, are unsuitable for analyzing this type of latent concept. LSA works in a way that is similar to the human brain works: It extracts the contextual meanings of a concept and identifies the complex structure between a latent concept and its relative words or terms [26].

To extract the key components of NPD curriculum from existing articles, the study utilized the package “lsa” for R [27] and the suggestion of a previous study [28] to performed LSA with the following steps.

Step 1: Text Preprocessing: It is one of the most elaborate steps to convert textual data to an appropriate format by using the following sub-steps.

  1. (1)

    Text cleanup is to remove unnecessary and meaningless elements, such as white space, stop words, and abbreviations.

  2. (2)

    Tokenization aims to identify meaningful keywords. Hence, the process includes splitting sentences into words, removing all punctuation marks from textual data, and giving words of text which is called tokens.

  3. (3)

    Stemming is the process of consolidating the different forms of a word into a standard representation, the stem. For instance, the words: ‘developed’, ‘development’, ‘developing’ could all be condensed to a common representation ‘develop’; and plurals to root like women to woman, men to man and horses to horse.

Step 2: Text Transformation: In general, the input of this step is bag-of-word (BOW) and it cannot be applied to the algorithms directly. The BOW should be transformed into the term-document matrix (TDM) which pit ‘terms (y-axis)’ against ‘documents (x-axis)’, and the cells give the amounts or frequencies of a term in a document. In addition, there are several methods can be used to find out the term importance.

Step 3: Feature Selection: To decide a subset of important features for use in model creation, the study utilized the Term Frequency inverted document frequency (TF-IDF) for filtering and removing redundant or irrelevant features. The function of TF-IDF is that calculating the relative frequency of words in a particular document compared to the inverse ratio of that word over the entire document corpus. This calculation establishes how relevant a given word to a specific document. Words that are prevalent in a single or a small portion of documents are prone to have higher TF-IDF numbers than common words such as articles and prepositions. Given that a document collection D, a word w, and an individual document \( d \in D \), the TF-IDF can be calculated as follows [28].

$$ w_{d} = f_{w,d} \times \log \left( {\frac{\left| D \right|}{{f_{w,D} }}} \right) $$

where:

\( f_{w,d} \):

Equals the number of times w appears in d;

\( \left| D \right| \):

Is the size of the corpus; and

\( f_{w,D} \):

Equals the number of documents in which w appears in D.

Step 4: Singular value decomposition (SVD): In this step, the TF-IDF weighted frequency-by-document matrix was decomposed using SVD, a factorization method. As the statement of prior literature [29], the calculation of SVD is based on a theorem from linear algebra, and a rectangular matrix A can be disassembled and produced three matrices—an orthogonal matrix U, a diagonal matrix S, and the transpose of an orthogonal matrix V:

$$ A_{mn} = U_{mm} S_{mn} V_{nn}^{T} $$

where \( U^{T} U = I, V^{T} V = I \), the columns of V are orthonormal eigenvectors of \( A^{T} A \), the columns of U are orthonormal eigenvectors of \( AA^{T} \). S is a diagonal \( {\text{m}} \times {\text{n}} \) matrix containing the square roots of eigenvalues from U or V in descending order.

Step 5: Factor reduction: In the previous step, SVD generated several latent topics. However, these topics are not equally important. Some topics contain more information and some contain less information. To reduce the number of factors and retain most of the information in the original text, one can restrict the matrix S to relatively higher eigenvalues and get a simplified matrix \( \hat{S}_{kk} \) by deleting rows and columns from S. For the matrix multiplication to go through, the corresponding row vectors of U and corresponding column vectors of V^T have to be removed and results in another two matrices \( {\hat{\text{U}}} \) and \( {\hat{\text{V}}} \). The result looks like this:

$$ \hat{A}_{mn} = \hat{U}_{mk} \hat{S}_{kk} \hat{V}_{kn}^{T} $$

where \( {\text{k}} < min\left( {m,n} \right) \), \( \hat{A} \) is an approximation matrix A.

Choosing a different k value will give different \( \hat{A}_{mn} \). This approximates the original matrix A and therefore captures more or less “trivial” topics.

Step 6: Factor Interpretation: The previous step generated several groups of topics with a unique level of prevalence (coherence) rate and a serial highly load terms that can identify specific meaning. Thereby, both authors utilized Bloom’s taxonomy action verbs and its synonym (see Table 20.1) to interpret these topics and inferred the key components of NPD curriculum independently. The identified topic labels in question are discussed with the third author to complete topic labels. The interpretation of the identified educational objectives is discussed in the following sections.

Results and Discussion

The dataset of textual data retrieved from ten journals related to the subject matter of the study included a total of 221 articles published between 2015 and 2020. Table 20.2 reported that the subject area of these articles was mostly business, management, and accounting (73.2%); engineering and computer science (18.7%); and decision science (7.3%). In addition, the main source journals based on the number of publications were: Journal of Product Innovation Management (22.4%), International Journal of Innovation Management (16.7%), Industrial Marketing Management (12.6%), International Journal of Production Research (10.2%) (see Table 20.2).

The Latent Semantic Analysis (LSA) provided further insight based on the re-search trend about the new product development into the topics of curriculum design. The study adopted ten topics, which offered an acceptable compromise between the level of prevalence and coherence. As shown in Table 20.3, the topics are defined by the factor loading of terms rather than by hard clustering a word may appear in more than one topic. The ten identified topics can be interpreted using Bloom’s Revised Taxonomy to disclose the implications of educational objectives.

Table 20.3 Summary of LSA results and interpretation
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The Latent Semantic Analysis (LSA) provided further insight based on the re-search trend about the new product development into the topics of curriculum design. The study adopted ten topics, which offered an acceptable compromise between the level of prevalence and coherence. As shown in Table 20.3, the topics are defined by the factor loading of terms rather than by hard clustering a word may appear in more than one topic. The ten identified topics can be interpreted using Bloom’s Revised Taxonomy to disclose the implications of educational objectives.

Consistent with previous findings [15], Table 20.3 revealed that the educational objectives of NPD course have been expanding across various fields, including innovation, product design, teamwork, engineering, manufacturing, and marketing. Therefore, the NPD curriculum is expected to facilitate the enhancement of students’ ability in innovating new products, collaborating with external stakeholders, and involving in open innovation. Besides, the ability of application of computer-based technology, such as CAD, man-machine interface, and data science, are deemed as major objectives of NPD course.

To infer the key components of NPD curriculum, the highly loaded terms of each topic are synthesized to create the corresponding domain knowledge and key component. Table 20.4 shows that the domain knowledge of NPD was classified into two categories as “field of business and management” and “field of engineering and computer science”. The field of business and management contains six domain knowledge, which is the foundation of new product development, including knowledge-based NPD, stakeholder engagement, sustainable development, lean principle, marketing management, and open innovation. On the other hand, the field of engineering and computer science focuses on practical application and the domain knowledge ranges from computer technology, text analytics, social media, and big data in business. The domain knowledge, however, is de-rived from the educational objectives and the key components of each domain knowledge were induced from the highly loaded term within each topic. There-fore, these key components of new product development, such as innovation management, knowledge management, supplier/customer involvement, and computer-aided design and manufacturing, not only align with the essentials of new product development but also facilitate educators and learners comprehending the full picture of the program and achieving the corresponding objectives.

Table 20.4 Key components of NPD curriculum
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Conclusion

Nowadays, under the fierce competition brought along by the globalization of the world economy, there are competitors all around the organization. For survival, therefore, the development of new products and services has become the essential capability, which encompasses concept design and the successful development of new products that can be launched in the market [4]. The process of new product development is highly challenging and uncertainly [1]. Therefore, a previous study by Mallick and Chaudhury [7] stressed that it is difficult to design an NPD curriculum that suits a practical purpose because the scope of NPD continuously expands across various fields.

Thus, collection and analysis of related literature are crucial to getting insight into the development trend in the future for product innovation and clarify the core components for curriculum design. To disclose the essentials of an NPD curriculum, the study performed the Latent Semantic Analysis to analyze collected literature on the subject matter. The results reveal that there are ten educational objectives must be considered for designing the NPD curriculum (see Table 20.3). Furthermore, as shown in Table 20.4, the domain knowledge corresponding to each educational objective was identified, and a serial key component of the NPD curriculum was derived from the domain knowledge.

In the field of business and management, there are six domain knowledge must be considered and brought into the NPD curriculum. At first, the management skills and knowledge, such as innovation management and knowledge management are deemed as the foundation of entrepreneurship education to enhance students’ ability to set up a new venture or develop and grow an existing business. Stakeholder engagement also is a crucial factor for reducing risk during new product development [15]. Therefore, the knowledge and skill of supplier involvement and customer involvement are the second key element of the NPD curriculum. Pursuing sustainable development and resilience is one of today’s most challenging tasks for management teams [25]. Thus, educating students with the knowledge of alliance and circular economy can promote their ability to attaining this goal. Finally, launching a new product efficiently is a crucial way to create organizational competition, regardless of its capacity and resource. Thus the knowledge and skill from product design, manufacturing and selling are the necessary components of the NPD curriculum.

In the field of engineering and computer science, the study highlights that the domain knowledge of the application of computer technology, text analytics, social network, and data science are important components of the NPD curriculum. As the statement from previous research [6], computer-aided design and manufacturing (CAD/CAM) can demonstrate and assembles the prototype in virtual space which reduces risks of new product development substantially. In addition, IT has been a powerful tool and widely applied to gather information from the relevant industry sector and customer [30]. Therefore, cultivating the ability about operation and manipulation of data science and social media is necessary for the NPD course.

The majority of existing NPD curricula tend to focus on theories and processes, rather than providing systematic methods and resources for the actual commercialization of ideas. The study presents several unique and important contributions to the education field. First, the study provides further insight into the trend of new product development which is expected to satisfy a growing interest in improving the learning performance of entrepreneurship education. Compared with the current entrepreneurship education program, the results of the study can be applied to design a comprehensive and systemic new product development program. Therefore, the NPD course not only provides students with entrepreneurial knowledge and skill but also encourages them to practice their capability by experiencing the new product development process.

However, the results and findings presented in this paper are based on the textual dataset retrieved from 221 articles that are related to the study. Hence, our future research will utilize this research method to analyze additional literature, and more information can be extracted for facilitating curriculum development and preparation work at school levels.